Calibration method using a Pitch-Catch arrangement for ultrasonic inspection of acoustically noisy materials

ABSTRACT

A method for the ultrasonic inspection of acoustically &#34;noisy&#34; specimens, such as those having intrinsically coarse or variable grain structure (e.g., turbine rotor parts made of superalloy compositions), employs a &#34;Pitch-Catch&#34; analysis wherein a &#34;through-transmitted&#34; sound wave is first acquired for a plurality of reference locations on the specimen and used as a calibration standard to normalize ultrasonic inspection test data for that specimen prior to flaw/defect detection and processing. The through transmitted sound wave is also used for accurately equating the amplitude of &#34;indications&#34; (i.e., significant detected ultrasonic reflections)to that of a standardized theoretical reflector of known size (e.g., an equivalent &#34;flat bottom hole&#34; or EFBH reflector) so that the test sensitivity or &#34;size of indications&#34; can be uniquely determined for each specimen on which the test is performed.

This is a divisional of application Ser. No. 08/149,208, filed Nov. 8, 1993 U.S. Pat. No. 5,445,029.

FIELD OF THE INVENTION

The present invention generally relates to ultrasonic inspection techniques for materials having an intrinsically coarse grain structure which results in anisotropic and nonuniform acoustic properties. More particularly, the invention relates to a calibration technique for "pitch-catch" ultrasonic testing that adjusts for variations in material properties and to an automated flaw/defect detection technique that employs a "floating" detection threshold wherein threshold levels are dynamically adjusted relative to the inherent acoustic noise structure of the specimen under test as opposed to an absolute threshold. Still more particularly, the invention relates to ultrasonic testing of solid disk superalloy forgings used in the construction of large turbine rotors.

BACKGROUND AND SUMMARY OF THE INVENTION

In many environments, the structural integrity of certain critical components of a particular system or apparatus is of the utmost importance in ensuring against future failures. In particular, the construction of large gas turbines imposes strict requirements on performance characteristics and reliability of the parts used. For example, components used in the construction of large gas turbines are typically subjected to great mechanical stresses and must be able to withstand continued exposure to extreme high temperatures, as well as, high velocity corrosive gas streams. One example of such critical components is the rotor of large gas turbines. Conventionally, superalloys (e.g., 40 Ni-15Cr-Ti-Nb) are utilized as suitable materials for the large solid disk forgings which make up a turbine rotor. To guarantee that the superalloy material quality is high and the structural integrity of rotor forgings is acceptable, special ultrasonic tests were developed to inspect each forging in the plane perpendicular to the highest operating stresses (i.e., the axial-radial plane). In particular, two ultrasonic testing techniques are conventionally used for the nondestructive testing of turbine rotor disk forgings near the highly stressed bore region: (1) a "Pitch-Catch" technique using two ultrasonic transducers, and, (2) a "Pulse-Echo Axial Long-Wave" technique that uses only a single transducer.

Ultrasonic Pitch-Catch testing per se is known and is commonly used to inspect machine components for material defects oriented perpendicular to the testing surfaces. However, in the past, these tests have been performed either uncalibrated (where simply the presence, but not the size of a defect is important), or a calibration was performed by using external blocks of material containing machined reflectors of a known dimension. Calibration references of this sort for conventional Pitch-Catch testing are listed in the nondestructive testing handbook and other reference tests, such as Krautkramer's Ultrasonic Testing of Materials. Unfortunately, these attempts at calibration, or the lack of calibration fail to compensate Pitch-Catch inspection data for variations in acoustic properties that are inherently present in many superalloy materials. More specifically, many superalloys are anisotropic and present nonuniform acoustic properties as a result of an intrinsically coarse grain structure. Consequently, such variations in the acoustic properties of superalloys affect the Pitch-Catch sensitivity, as well as the ability to estimate the size of a detected defect from its reflected signal amplitude.

A further disadvantage of not calibrating a Pitch-Catch test procedure is that no size information is provided following detection of a defect. In addition, the sensitivity of the test would be unknown. Without some estimate of defect dimensions, structural analysis cannot be accurately performed to determine the severity of such a defect on the mechanical performance and reliability of the particular component pan.

In the alternative, if some external material is used for calibration, the relationship established in the external reference will not be applicable to the particular forging specimen under test. This is because due to their highly nonuniform properties, no two superalloy forgings are alike. In fact, acoustic properties within the same forging may vary considerably. Therefore, an external calibration standard, even using similar material, would fail to completely characterize the specific forging specimen being tested. In addition, many combinations of forging sizes and calibration reference reflectors would be required to address all components of a particular product line. Moreover, the effective changes in engineering requirements on test sensitivities would be difficult or impossible to predict.

In accordance with the present invention, a calibration technique is provided for conventional Pitch-Catch ultrasonic testing procedures that adjusts for variations in material ultrasonic test properties. More specifically, in accordance with the calibration technique of the present invention, "through-transmitted" sound waves are collected prior to the Pitch-Catch diagnostics on the forging and used to normalize all subsequently collected Pitch-Catch inspection data. In addition, measured amplitudes of potential fault indications ("indication amplitudes") are equated to a known reference defect (e.g., an equivalent flat bottom hole) by a particular relationship (discussed further herein) based on the through transmitted sound wave, component thickness and the ultrasonic test specimen/material characteristics.

Since the through-transmitted sound wave is affected by the material acoustic properties in the same way that the inspection test data is affected, it can be used to normalize the inspection data prior to automated defect detection or sizing. In addition, using the through-transmitted sound wave to equate the amplitude of defect indications to a known sonic reflection standard, such as an FBH reflector, allows the current test sensitivity (size of indications) to be determined uniquely for each Pitch-Catch test conducted. Using a through-transmitted sound wave in this manner provides a means to uniquely compensate for variations in acoustic properties from forging to forging as well as within any given forging.

In addition to the specific above-mentioned problems inherent to Pitch-Catch diagnostics, prior art ultrasonic inspection techniques of all types prove difficult (if not impossible) to adjust flaw/defect detection threshold levels to always obtain an optimized sensitivity for testing acoustically noisy materials. Ultrasonic inspection systems conventionally rely on an expected echo-dynamic pattern associated with the reflection of ultrasound from a defect as the sound beam traverses it. The prior art ultrasonic flaw/defect conventional flaw detection and recognition methods as employed in Pitch-Catch, Pulse-Echo or other diagnostic techniques, in general, either use a fixed predetermined amplitude as a defect recognition threshold, or use no threshold at all. In systems using fixed thresholds, the threshold is adjusted to a level that is determined by the test system operator based on a known reflector size or set to a level slightly higher than an approximation of a general (average) noise level observed in the material.

Consequently, when testing acoustically noisy components like turbine rotor disks, if the detection criterion is based solely on the expected echo-dynamic pattern from a flaw/defect, and no thresholds are used, an abnormally high number of false defect indications are encountered as a result of the nonuniform distribution of acoustic noise within the component material. This is due to the fact that acoustic noise patterns in various superalloy materials used in turbine rotors are coherent enough (i.e.. have the proper echo-dynamic characteristics) to actually appear as real defect indications. Accordingly, the echo-dynamic characteristics of such materials make the use of amplitude detection thresholds absolutely necessary when testing turbine rotor forgings of other parts which use superalloy materials. However, because the noise structure in rotor forgings is typically nonuniform, not only between two separate forgings but within single forgings as well, selection of an absolute threshold value is not feasible. It would, invariably, require the setting of some arbitrary threshold quite high above observed noise peaks to eliminate false alarms. Obviously, such a setting does not provide optimum test sensitivity. Accordingly, for the purpose of testing turbine rotor forgings and other components made of superalloys or other acoustically noisy materials, it would be highly desirable to have a testing system which could dynamically optimize the test sensitivity. An improved automatic flaw/defect scanning and detection technique in accordance with the present invention solves this problem by providing the capability to dynamically adjust the flaw/defect detection threshold level so as to instantly and automatically respond to changing noise patterns. Moreover, the improved technique is readily applicable to both Pitch-Catch and Pulse-Echo diagnostics as well as other techniques, as will be recognized by one of ordinary skill in the art upon reading the following description of the invention.

In accordance with the improved automatic flaw/defect scanning and detection technique of the present invention, a "rolling average" of digital ultrasonic inspection (measurement) data is used to estimate the "local" noise level and compute a unique signal-to-noise (S/N) ratio for every data point (i.e., transducer pulse) generated. Variations in the S/N ratio for the material are measured at each axial slice of material volume inspected. A predetermined function of the standard deviation of the calculated S/N ratio values is then used to continuously adjust the detection amplitude threshold to dynamically optimize the defect detection criterion and minimize false alarms. This predetermined detection threshold function, as discussed in greater detail further herein, can also be varied to accommodate the particular type of test being performed (i.e., pitch-catch, axial long-wave. etc. ). Subsequent additional processing of sequential S/N values is then performed to determine whether a recorded internal reflection, i.e., a "target," meets a particular predetermined criteria for a defect indication. The echo-dynamic behavior of the S/N values must, therefore, correspond to a dynamically custom-tailored "expected" response from a target to be reported as a defect indication. Thus, the automatic flaw/defect detection technique in accordance with the present invention provides increased defect detection sensitivity over conventional methods and continuous automatic adjustment of the detection threshold based on the particular intrinsic material properties of the part being inspected.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features and advantages of the present invention will become more completely understood by referring to the following detailed description of presently preferred exemplary embodiments in conjunction with the FIGURES in which like reference numerals refer to like elements throughout:

FIG. 1 is a schematic block diagram of an ultrasonic inspection system for the automated nondestructive testing of turbine rotor disk forgings in accordance with a preferred exemplary embodiment of the present invention;

FIGS. 2A and 2B are, respectively, front and side schematic views illustrating a Pitch-Catch test set-up for performing ultrasonic measurement on a turbine disk forging;

FIG. 3A is a diagrammatic illustration of the orientation of ultrasonic transducer units on a rotor disk forging during a Pitch-Catch test procedure;

FIG. 3B is an illustration of a CRT display showing the peak amplitude of an exemplary defect indication obtained using the transducer configuration shown in FIG. 3A;

FIG. 4A is a diagrammatic illustration of the orientation of transducers on a turbine rotor disk forging for obtaining through-transmitted sound wave data for normalization of Pitch-Catch test measurement data;

FIG. 4B is an illustration of a CRT display showing the peak amplitude of a reference through-transmitted sound wave signal obtained using the transducer configuration shown in FIG. 4A;

FIG. 5A is a diagrammatic illustration of a single transducer scanning arrangement of a turbine rotor disk forging;

FIG. 5B is an illustration of a CRT display showing an exemplary echo-dynamic response pattern of a defect during eight consecutive ultrasonic pulses for the scanning arrangement of FIG. 5A;

FIG. 6A is a diagrammatic illustration of an ultrasonic scanning arrangement for accomplishing S/N averaging over an arcuate region of a turbine rotor disk forging;

FIG. 6B is a schematic diagram of a side view of a disk rotor forging illustrating the arcuate distance on either side of a transducer over which a localized average noise level is obtained for each measurement.

DETAILED DESCRIPTION OF THE DRAWINGS

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system components, equipment, diagnostic techniques, exemplary computer program flow steps, etc., in order to provide a thorough understanding of the present invention. However, it will be apparent to one skilled in the an that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well known methods and programming procedures, devices, and circuits are omitted so not to obscure the description of the present invention with unnecessary detail.

Referring to FIG. 1, a schematic diagram of an exemplary ultrasonic testing and measurement system 100 for the inspection of gas turbine rotor parts is shown. A turbine disk rotor forging 110 under test is rotated on a mechanical drive system 120. Inspection data is acquired in the form of ultrasonic echoes gated from transducer units 125 and 126 via a logarithmic ultrasonic pulser/receiver instrument 140 and digitally processed by computer/data acquisition system 130 with amplitude and polarity information being preserved. The data acquisition system used in practicing the present invention may be, for example, a conventional personal computer system with keyboard, display and monitor (equipped, for example, with servo motion control boards, such as a Galil 3-Access 600 series motion control board, and an analog-to-digital converter card, such as a Sonix 8100 A/D board). Pulser/receiver 140 (for example, a GE Amput pulser/receiver instrument) provides excitation signals to transducer units 125, 126 and sends received (detected) ultrasonic echo signals from transducer units 125, 126 to an analog-to-digital convertor (not shown) within data acquisition system 120. Pulser/receiver 140 may also be provided with a CRT (141) for displaying ultrasonic signals picked up by transducers 125, 126.

Trigger input line 131 provides pulser/receiver 140 with timing signals from computer/data acquisition system 130. Received ultrasonic signals are provided to the data acquisition system via line 132. An analog-to-digital (A/D) converter within the data acquisition system digitizes all analog measurement signals provided by pulser/receiver 140. Transducers 125, 126 are supported on respective probe support towers 127, 128, which provide dual axes (x-y) scanning movement capability. Mechanical drive rotator 120 and support tower dual axes drive servos (not shown) are controlled by data acquisition system 130 via motion control amplifiers 150. A printer, 160, or other output and storage devices may also be connected to computer/data acquisition system 130.

Although ultrasonic testing system 100 is configured specifically for testing gas turbine disk forgings rotated on a mechanical drive system, the transducers, transducer housing/coupling support mechanism and scanning arrangements may be modified to accommodate different components, testing procedures and applications. For example, certain testing procedures require a pair of transducers (e.g., a Pitch-Catch test), while other procedures require the use of only a single transducer (e.g., a Pulse-Echo Axial Long-Wave test).

Referring now to the schematic views shown in FIGS. 2A-3B, the basic set-up for a Pitch-Catch test procedure is discussed. Briefly, two "angled beam" transducer units T1 and T2 (i.e., a transducer in a predetermined angled acoustic coupler/housing) are placed on opposite side surfaces of rotor disk forging 200. Transducers T1 and T2 are operated in a transmit-receive mode and directed toward an axial-radial plane of the forging. Forging disk 200 is then rotated by a mechanical drive mechanism and as the forging rotates, its axial-radial planes 201 pass through the beam path 202 intersection creating an "inspection volume." (For example, after a single rotation, a toroid of material has been inspected.) Transducer units T1 and T2 are swept radially in unison to complete the inspection of one axial slice (i.e., plane) of material. To complete the process, transducer units T1 and T2 are also moved relative to each other so that the beam path intersection 202 moves axially across the forging. FIG. 3A shows the orientation of the angled beam transducer units (301 and 302) positioned on opposite side surfaces of disk rotor forging 200 and illustrates the sound path legs (1 and 2) of an exemplary ultrasonic beam incident upon a detected defect (or "target") 303. FIG. 3B illustrates an exemplary pulser/receiver unit CRT display of the peak amplitude, P, of defect/indication 303 in FIG. 3A.

Referring now to FIG. 4A, an improved calibration method for Pitch-Catch testing in accordance with the present invention is accomplished by rotating one of the transducer units by 180° and displacing it by approximately the forging thickness, T, so that both transducers T1 and T2 are aiming directly at each other. The ultrasonic beam path 3 passes uninterrupted from transducer unit 402 to transducer unit 401 and peak signal obtained is referred to as the "through transmitted sound wave." The placement of units 401 and 402 is adjusted to maximize the amplitude of the through-transmitted sound wave. Angle θ is measured and used in defect detection "sizing equation" (discussed below) along with the maximize amplitude of the through-transmitted sound wave. FIG. 4B illustrates an exemplary pulser/receiver CRT display of the peak reference amplitude. P_(r), of the through-transmitted wave traveled along the path (3) in FIG. 4A.

Although the maximum sound pressure relative to a defect is typically obtained at 45°. in accordance with a presently preferred exemplary embodiment of the present invention, a slightly lower angle of 40° is used because it shortens the sound path distance within the forging, and hence lowers the attenuation of sound between the transducer units. Prior to performing the actual Pitch-Catch inspection, a unique through-transmitted sound wave (i.e., the thru-wall reference signal) is obtained at many "reference" locations on the forging. The through-transmitted wave reference signal obtained at a location nearest to each Pitch-Catch test data point is then divided into the Pitch-Catch data to normalize it prior to any post-processing.

Moreover, since certain superalloy materials are considerably bandpass sensitive, the Fourier Transform of the through-transmitted reference signal is computed and compared to the transducer unit's unfiltered bandpass. Before testing, the filtered and unfiltered bandpasses are matched as closely as possible in order to maximize the test sensitivity. In addition, a "scan plan" is determined prior to testing based on the forging dimensions and transducer unit frequency. The "intersection beam" dimensions are calculated by conventional techniques for each location in the forging and the scan plan is controlled to produce a near uniform sound field within the inspection volume.

In accordance with the present invention, a defect "sizing equation" is used to determine an equivalent flat bottom hole (EFBH) reflector diameter, D_(f), of a defect indication based on parameters such as the peak amplitude of reflected sound, the amplitude of the through-transmitted reference signal at the location of the indication, and other known or conventionally calculated quantities. In the present invention, D_(f) is calculated using the sizing equation, EQU. (1), immediately below, by computer/data acquisition system 130: ##EQU1## where P=peak amplitude of the indication

P_(r) =amplitude of thru-wall reference signal location of the indication

v=shear wave velocity of sound in the material

z=distance of the indication from the nearest surface of the forging (known from beam intersection print calculations)

T=axial thickness of the forging

f=measured frequency of the thru-wall reference signal

θ=measured intercept angle between the search units

In addition, to account for the effects of the nonlinear on-axis sound pressure distribution near the transducer (i.e., "near field" effects), a correction is applied to the EFBH diameter determined above. The corrected diameter, D_(fc), is calculated by computer/data acquisition system 130 using EQUATION (2) immediately below (subscript references represent the sound path legs identified in FIGS. 3A and 4A): ##EQU2##

As explained above, in accordance with the present invention, the Pitch-Catch data is normalized by the amplitude of thru-wall reference signals to adjust for acoustic variations in components under test resulting from, for example, the grain structure of the material or surface condition of the pan. However, for a "Pulse-Echo" Axial Long-Wave type diagnosis, only a single transducer is used and, prior to any subsequent processing, the acquired data is normalized by an internal reference reflection obtained from the rotor disk forging side wall opposite the transducer (i.e., a "back wall" reflection).

An automatic flaw detection technique for ultrasonic inspection system 100 that has a dynamically adjusting detection threshold capability in accordance with the present invention, and is applicable to both Pitch-Catch and Pulse-Echo diagnoses as well as other conventional techniques, is now discussed with respect to FIGS. 5A-6B.

Referring first to FIG. 5A, a diagram of a generalized test set-up for ultrasonic diagnosis of a turbine rotor disk forging (200) in accordance with the present invention is illustrated. Although FIG. 5A depicts only the single transducer arrangement conventionally associated with a Pulse-Echo diagnosis, the scanning/pulsing technique basically illustrated therein and described below is applicable to Pitch-Catch and other types of ultrasonic diagnosis as well. During data acquisition scanning, ultrasonic transducer 501 is pulsed at a repetition frequency sufficient to produce eight pulses as its 6 dB sound beam width traverses any given point in the material as indicated by scale 502. As illustrated in FIG. 5B, which shows an exemplary pulser/receiver CRT display of a defect scanned with eight consecutive ultrasonic pulses each having a 6 dB beam width, this scanning/pulsing arrangement results in at least eight responses (510) from any flaw/defect. A 6 dB sound beam width is chosen so that the echo-dynamic response pattern obtained will approximately rise and fall by a factor of two, as illustrated by the respective amplitudes of the eight pulse waveforms shown in FIG. 5B.

For each transducer pulse, a "rolling average" is computed to calculate the local noise level over approximately a six-inch arc along the arcuate scan direction (illustrated in FIG. 6B). As shown in FIG. 6A, the beam intersection width (600) is left out of averaged areas, N_(a) and N_(b), so that the insonified target does not interfere with the noise calculation. In FIG. 6B, arcs 502 and 503 represent two separate arcuate data regions (each is approximately 3") over which local noise is averaged on either side of transducer unit 501. Each increment in the direction of the sound wave propagation, called a "plane of data," is treated independently in these rolling average noise calculations. This rolling average calculation of data also acts as an effective filter for changes in the scan responses due to, for example, the initial ultrasonic pulse, attenuation decay and standing waves. For each digital point (or pulse of the transducer), defined as i, the local noise level, N_(i), is calculated by computer/data acquisition system 130 using EQUATION (3) immediately below from the signal amplitude, S_(n), acquired at each measurement point in the inspection: ##EQU3## where b=6 dB beam width in the scan direction and

n=total number of data points in the 6" average

Next, a signal-to-noise ratio for each point [S/N]_(i), is calculated by dividing the signal amplitude at point i, S_(i), by the local noise level N_(i). In this manner every digital data point acquired within a given data plane is converted into a S/N value (see FIG. 6A).

The detection threshold for the plane is then computed as a function of the standard deviation, σ, of the S/N values. The standard deviation, σ, is computed by computer/data acquisition system 130 using the following equation: ##EQU4## where n=total number of data points in plane

Exemplary detection thresholds for each type of diagnosis are set as follows:

    __________________________________________________________________________     For:                                                                            Pitch-Catch Test:                                                                           Detection Threshold = 1 + 2σ                                Axial Long Wave Test                                                                        Detection Threshold = 1.3x(1 + 2σ)                                                         Near Field                                                              = 1.1x(1 + 2σ)                                                                  Elsewhere                                      __________________________________________________________________________

Based on the expected "persistence" (i.e., pulses per beam width) of a valid target, a detection is considered if eight consecutive values of S/N equal or exceed the detection threshold.

An indication threshold, equal to twice the detection threshold, is used to ensure that the detection has the expected echo-dynamic pattern of a valid target. Because the transducer was pulsed eight times per 6 dB beam width, at least one point in the detected S/N group must equal or exceed the indication threshold.

Procedural steps for implementing a Pitch-Catch Ultrasonic diagnostic test in accordance with the present invention, using an ultrasonic inspection system as depicted in FIG. 1 and including exemplary computer program flow steps, are set forth immediately below:

    ______________________________________                                         Step 1:                                                                              Position the transducers on the part to obtain a through-                      signal.                                                                        Set signal sensitivity by adjusting the gain.                                  Using this through-signal, acquire a reference set of data                     by pulsing once per degree in concentric revolutions                           spaced one inch apart over the inspectable portion of the                      part.                                                                    Step 2:                                                                              Plan a scan of the part so that data will be acquired in a                     Pitch-Catch manner. (The targeted position of a pulse                          will fall on an axial plane. Axial planes are spaced on                        3 dbK beam width apart. The target positions will, thus,                       be arranged in concentric revolutions within the plane                         spaced one 3 dbK beam width apart. Along a revolution,                         the "targets" will be one-eight of a 6 dbK beam width                          apart).                                                                  Step 3:                                                                              Acquire the axial planes of Pitch-Catch data. For each                         pulse a single peak is obtained.                                         Step 4:                                                                              Determine the Maximum and Average Signal-to-Noise                              Ratio for each axial plane of data in the following                            manner:                                                                        Loop over each axial plane.                                                     Initialize the number of non-noise spike peaks in the                          plane to zero.                                                                 Initialize the Sum of S/N ratios for the plane to zero.                        Initialize the Maximum S/N ratio for the plane to zero.                        Loop over each revolution of a plane.                                           Loop over each peak of a revolution of a plane.                                 Normalize the peak using the nearest reference                                 Validate that the normalized peak is not a noise                                spike--a spike will be greater than three times                                the normalized amplitudes of the peaks on either                               side--ignore any noise spikes                                                 Add valid peaks to the number of peaks in a plane.                             Using the running average approach, determine                                   the local noise of this peak (Ni)                                             Calculate the signal-to-noise ratio for this peak.                             Compare with the Maximum Signal-to-Noise Ratio                                  for the plane so far and if this peak's exceeds,                               save the new maximum.                                                         Add the S/N ratio for this peak to the Sum of S/N                               ratios for this plane.                                                      End Loop over each peak of revolution of plane.                               End Loop over each revolution of plane.                                        Calculate the Average Signal-to-Noise Ratio for this                            plane using the Sum of Signal-to-Noise Ratios for this                         plane and the number of valid peaks in the plane. The                          Average Signal-to-Noise Ratio is, as expected,                                 essentially equal to 1.0.                                                     End loop over each axial plane.                                          Step 5:                                                                              For each axial plane calculate the Noise Threshold for                         the plane. This Noise Threshold is equal to the Average                        Signal-to-Noise Ratio for the plane plus two standard                          deviations.                                                              Step 6:                                                                              Evaluate each axial plane of data looking for flaw                             indications in the following manner.                                           Loop over each axial plane.                                                     Skip any plane whose Maximum Signal-to-Noise Ratio                              for that plane is less than twice the Noise Threshold                          for that plane.                                                               For a plane not skipped, loop over revolutions of the                          plane                                                                            Loop over normalized peaks of revolution of plane                               Using the running average approach determine                                    the local noise of this peak.                                                 Calculate the S/N ratio for this peak.                                         For any peak whose SIN ratio is above the                                       Noise Threshold for the plane, build a set of                                  peaks along the revolution. If the set of peaks                                builds up to equal or exceed the 6 dbk beam                                    width, then declare this group as part of an                                   indication and send it into a nearness algorithm                               which builds up indications.                                                End loop over normalized peaks of revolution of                                plane.                                                                       Loop over each axial plane.                                              Step 7:                                                                              As the nearness algorithm building groups of peaks                             determines that the set for an indication is closed, the                       indications are given a flaw size based upon the location                      of the indication. This flaw size is reported with the                         location within the part.                                                ______________________________________                                    

Procedural steps for implementing a Pulse-Echo Axial Long-Wave ultrasonic diagnostic test in accordance with the present invention, using an ultrasonic inspection system as depicted in FIG. 1 and including exemplary computer program flow steps, are set forth immediately below:

    ______________________________________                                         Step 1:                                                                              Position the transducer on the part to obtain a Pulse-                         Echo signal; Set signal sensitivity by adjusting the gain.               Step 2:                                                                              Plan a scan of the part so that waveforms of data will be                      acquired in a Pulse-Echo manner. (The waveforms are to                         be collected by scanning in concentric revolutions on the                      surface of the inspectable portion of the part. The                            revolutions are to be spaced twice the near field beam                         width apart and the ultrasonic pulses are also to be                           spaced that same distance apart along a revolution. The                        waveform should be acquired at 25 MHz sampling rate to                         one inch beyond the backwall reflection of the part. The                       peak at the backwall is saved for every pulse as a                             reference through signal for that pulse. The waveform is                       then compressed into bins each representing an axial                           quarter inch of depth. Only the peak within each bin of                        the waveform is saved. A zoned approach is then applied                        to the waveform. The bins of the waveform are each                             associated with a zone. A zone is referenced to its                            distance from the transducer and its relationship with the                     near field zone of the transducer. Each zone has an                            expected pulse interval for an indication to be valid. It is                   only necessary to save enough waveform zones within a                          location on the part to meet the expected pulse interval                       within the beam spread. Based on the location of the                           transducer the saved zones of this waveform pulse are                          determined. Every bin within the near field zone is saved                      on every pulse. For instance, the expected pulse interval                      within this zone is "two". Accordingly, it is necessary                        only to recognize two pulses with normalized peaks                             within the near field zone having a signal-to-noise ratio                      above the noise threshold to call an "indication" at that                      location).                                                               Step 3:                                                                              Acquire the set of compressed zoned waveforms in the                           Pulse-Echo manner.                                                       Step 4:                                                                              Break apart the compressed zoned waveforms into axial                          planes of data similar to that which would have been                           collected during the Pitch-Catch test. Each plane of data                      is spaced a quarter inch apart. The spacing of                                 revolutions and the peaks along a revolution are                               uniform as the result of the design of the zoning                              algorithm. The backwall reference for each peak in a                           plane is known.                                                          ______________________________________                                    

From this step on (i.e., once the data has been broken up into axial planes) the evaluation of the data is now very similar to the method used on the Pitch-Catch test. One difference is that three levels of Noise Threshold are calculated; a Low noise threshold using two standard deviations as in the Pitch-Catch test, a Mid noise threshold using three standard deviations and a Hi noise threshold using four standard deviations. The noise threshold calculation is then based on the zone that the plane lies in. A multiplier of 1.3 times is applied to the near field zone planes and a multiplier of 1.1 for all other zones. Another variation lies in the algorithm for testing the association of points to form an indication group. There are three classes of sets, each using one of the levels of noise threshold, and a different association criteria. (Noise spikes are typically not a problem in this test).

    ______________________________________                                         Step 5:                                                                              Determine the Maximum and Average S/N ratio for each                           axial plane of data in the following manner:                                   Loop over each axial plane.                                                      Initialize the number of non-noise spike peaks in the                           plane to zero.                                                                Initialize the Sum of S/N ratios for the plane to zero.                        Initialize the Maximum S/N ratio for the plane to                               zero.                                                                         Loop over each revolution of a plane.                                           Loop over each peak of a revolution of a plane.                                 Normalize the peak using the backwall                                           reference                                                                     Add this peak to the number of peaks in a                                       plane.                                                                        Using the running average approach,                                             determine the local noise of this peak (Ni)                                   Calculate the S/N ratio for this peak.                                         Compare with the Maximum S/N ratio for the                                      plane so far and if this peak's exceeds, save                                  the new maximum.                                                             Add the S/N ratio for this peak to the Sum of                                    S/N ratios for this plane.,                                                 End Loop over each revolution of plane.                                        Calculate the Average S/N ratio for this plane                                  using the Sum of S/N ratios for this plane and                                 the number of valid peaks in the plane. the                                    Average S/N ratio is, as expected, essentially                                 equal to 1.0.                                                               End loop over each axial plane.                                          Step 6:                                                                              For each axial plane, calculate three Noise Thresholds                         for the plane. The Lo Noise Threshold is equal to the                          Average S/N Ratio for the plane plus two standard                              deviations. the Mid Noise Threshold uses three standard                        deviations and the Hi Noise Threshold uses four standard                       deviations. The zone which the axial plane belongs to                          then applies a multiplier of 1.3 for the near field zone                       and 1.1 for all other zones.                                             Step 7:                                                                              Evaluate each axial plane of data looking for flaw                             indications in the following manner:                                           Loop over each axial plane.                                                     Skip any plane whose Maximum S/N Ratio for that                                 plane is less than the Lo Noise Threshold for that                             plane.                                                                        For a plane not skipped, loop over revolutions of the                          plane                                                                           Loop over normalized peaks of revolution of plane                               Using the running average approach determine the                                local noise of this peak.                                                     Calculate the S/N Ratio for this peak.                                         For any peak whose S/N Ratio is above the Noise                                 Threshold levels for the plane, build a set of                                 peaks along the revolution, taking neighboring                                 revolutions into consideration. If the set of peaks                            builds up to either equal or exceed the 6 dbk                                  beam width and the noise level based neighbor-                                 ing revolution criteria are met, then declare this                             group as part of an indication and send it into a                              nearness algorithm which builds up indications.                              End Loop over normalized peaks of revolution of                                plane.                                                                        Loop over revolutions of the plane.                                           Loop over each axial plane.                                              Step 8:                                                                              As the nearness algorithm building groups of peaks                             determines that the set for an indication is closed, the                       indications are given a flaw size based upon the location                      of the indication. This flaw size is reported with the                         location within the part.                                                ______________________________________                                    

While the present invention has been described and illustrated in connection with what is presently considered to be the most practical and preferred embodiments, it should be understood that the present invention is not limited thereto since modifications may be made by persons skilled in the art. The present invention contemplates any and all modifications and equivalents that fall within the spirit and scope of the underlying invention disclosed and claimed herein. 

What is claimed is:
 1. In a nondestructive testing system for performing Pitch-Catch ultrasonic inspections, including a data acquisition system for acquiring and analyzing ultrasonic signal measurement data, a method for automatically calibrating said measurement data to compensate for variations in acoustic properties within a specimen under test, comprising the steps of:(a) positioning at least one pair of ultrasonic transducers on opposing surfaces of said specimen under test in a configuration such that a non-reflecting through-transmitted ultrasonic wave is transmitted between said transducers; (b) obtaining through-transmitted wave reference signal data for a plurality of reference locations on said specimen: (c) positioning said pair of transducers on said opposing surfaces in relative positions such that Pitch-Catch diagnostics is performed and acquiring ultrasonic measurement data at a plurality of monitored locations on said specimen; (d) normalizing the measurement data acquired in step (c) for each of said plurality of monitored locations by dividing the measurement data acquired at each of said plurality of monitored locations by corresponding through-transmitted wave reference signal data obtained at a reference location nearest to each of said plurality of monitored locations.
 2. A method for automatically calibrating measurement data for Pitch-Catch ultrasonic inspections in a nondestructive testing system according to claim 1, wherein said through-transmitted ultrasonic wave is introduced into said specimen under test at a angle of less than 45° from perpendicular to a surface of said specimen.
 3. A method for automatically calibrating measurement data for Pitch-Catch ultrasonic inspections in a nondestructive testing system according to claim 1, wherein said through-transmitted ultrasonic wave is introduced into said specimen under test at a angle of 40° from perpendicular to a surface of said specimen.
 4. The method as set forth in claim 1, wherein a first transducer of said pair of transducers in step (a) is displaced along one surface of said specimen from a position directly opposite a second transducer of said pair of transducers by a distance corresponding substantially to a thickness of said specimen local to said pair of transducers.
 5. In a nondestructive testing system for performing ultrasonic inspections on acoustically variant materials, including a data acquisition system for acquiring and analyzing ultrasonic signal measurement data, a method for automatically calibrating said measurement data to compensate for variations in acoustic properties within a specimen under test, comprising the steps of:(a) obtaining through-transmitted ultrasonic wave reference data for a plurality of reference locations on said specimen; (b) acquiring ultrasonic measurement data at a plurality of monitored locations on said specimen; (c) normalizing the measurement data acquired in step (b) for each of said plurality of monitored locations by dividing the measurement data acquired at each of said plurality of monitored locations by corresponding through-transmitted wave reference data obtained at a reference location nearest to each of said plurality of monitored locations.
 6. A method as set forth in claim 5, wherein through-transmitted ultrasonic wave reference data is acquired by positioning a pair of transducers on opposing surfaces of said specimen and a first transducer of said pair of transducers is displaced along said specimen surface from a position directly opposite a second transducer of said pair of transducers by a distance corresponding substantially to a thickness of said specimen local to said pair of transducers.
 7. A method as set forth in claim 5, wherein said through-transmitted ultrasonic wave is introduced into said specimen under test at a angle of 40° from perpendicular to a surface of said specimen.
 8. A method as set forth in claim 5, wherein ultrasonic measurement data is acquired by positioning said pair of transducers on opposing surfaces of a specimen in relative positions such that Pitch-Catch diagnostics is performed and performing a Pitch-Catch ultrasonic measurement at each of said plurality of monitored locations. 